The present disclosure relates generally to a building management system and more particularly to building information management of a building management system that collects, manages, and utilizes data for interconnected devices and other entities.
In a typical building management systems, relationships between spaces, assets, and/or people are usually pre-defined and generally have a hierarchical organization. This can lead to many deficiencies. For example, any change in the relationships between spaces, assets, and/or people may require underlying databases and/or programs of the building management system to reconfigure the relationships with external user intervention. This does not allow the BMS to naturally and automatically adapt to changes in usage, systems, and/or operating conditions. Furthermore, this also requires specific programming paradigms to be inbuilt into the building management system to allow for these changes. The exception handling scenarios in building management system for any deviation from expected semantic interpretation of data around spaces, assets, and/or people can become cumbersome and complicated, often leading to downstream erroneous data transmission and information processing. The prevalent approach based on linear associations also do not allow for multi-dimensional dynamic and simultaneous analysis of building information around spaces, assets, and/or people for different types of analysis and simulation insights. The increasing usage of artificial intelligence influenced analytical techniques which are not based on heuristics require a more flexible organization of information.